North Wingfield and Holmewood Crime Rate

North Wingfield and Holmewood’s crime data reveals a stark contrast in trends: while overall crime remains stable, bicycle theft has surged by 100% year-on-year. The area’s crime rate of 106.7 per 1,000 residents, 17% above the UK average, highlights the need for targeted safety measures. Notably, property crime is 15.9% below the UK average, yet violence and sexual offences remain disproportionately high, reflecting complex local dynamics.

North Wingfield and Holmewood is a built-up area within North East Derbyshire, characterized by a mix of residential and commercial properties. Its proximity to commuter routes and local amenities may contribute to higher levels of anti-social behaviour and property crime. The area's demographic profile, including a significant student population and older residents, likely influences crime patterns, with vehicle crime and burglary being more prevalent in areas with transient populations.

The most surprising finding is the 100% year-on-year increase in bicycle theft, despite remaining 50% below the UK average. This could reflect targeted thefts near local schools or colleges, where bikes are frequently left unattended. Violence and sexual offences, at 47.4% of all crimes, are 57% above the UK average—likely tied to the area’s mix of young adults and transient populations. Anti-social behaviour, 9% above the UK average, may stem from late-night activity in local pubs or social hubs. Notably, shoplifting and vehicle crime are both below the UK average, suggesting effective local deterrents or lower retail footfall compared to urban centres.

Crime in North Wingfield and Holmewood has remained stable (-0.5% YoY), but key subcategories show sharp divergences. Bicycle theft has surged by 100% YoY, likely due to targeted thefts near schools or colleges. Meanwhile, criminal damage and arson have fallen by 8%, possibly reflecting seasonal factors or reduced public gatherings. Other theft and shoplifting have also declined slightly, though both remain above the UK average. The area’s property crime rate is 15.9% below the UK average, suggesting effective local deterrents or lower retail footfall.

How To Keep Safe in North Wingfield and Holmewood

Avoid leaving bicycles unattended near local schools or pubs, as theft has surged by 100% YoY. Secure vehicles in well-lit, monitored areas to mitigate the 52% rise in vehicle crime. For residents, use Neighbourhood Watch schemes to report anti-social behaviour, which is 9% above the UK average. Avoid isolated paths after dark, as vehicle crime peaks between 12am and 6am. Consider installing motion-activated lights to deter burglars, which are 7% above the UK average.

Crime in North Wingfield and Holmewood peaks in the afternoon (12pm–6pm), with theft accounting for 48% of crimes during this period, likely linked to retail activity. Vehicle crime rises sharply at night (12am–6am), with 29% of crimes occurring during these hours, possibly due to isolated parking areas. The evening (6pm–12am) sees a 20% spike in theft, correlating with increased foot traffic and nightlife. Burglary, however, is most common at night (21%), reflecting opportunistic entries in quieter residential areas.

North Wingfield and Holmewood’s crime rate of 106.7 per 1,000 is 114% higher than Pilsley and Lower Pilsley (49.8 per 1,000), likely due to Pilsley’s more rural character and lower population density. Conversely, Grassmoor has a 7% higher rate, potentially linked to its urban infrastructure and higher transient population. Old Tupton, with a rate 19% lower, may benefit from stronger community engagement or lower socioeconomic challenges.

For North Wingfield and Holmewood’s crime profile, scOS’s proactive boundary detection and vehicle registration verification are critical. With vehicle crime rising 52% YoY, scOS’s DVLA checks can flag stolen plates approaching properties. For burglary, scOS’s AI monitoring and automated lighting deter intruders, especially during late-night peaks when 29% of vehicle crimes occur. Its behavioural pattern learning also reduces false alarms, a key benefit in areas with high anti-social behaviour.